{"id":593445,"url":"https://alion.io/job/accenture-data-architect-10","title":"Data Architect","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2085,"ghost_share":0.001,"stale_share":0.141,"repost_share":0.006,"time_to_fill_p50_days":5,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":34000,"max_usd":65000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":true},{"name":"C++","optional":true},{"name":"CNN","optional":true},{"name":"Computer Vision","optional":true},{"name":"Docker","optional":true},{"name":"Edge AI","optional":true},{"name":"GStreamer","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Linux","optional":true},{"name":"Localization","optional":true},{"name":"Machine Learning","optional":true},{"name":"Model Distillation","optional":true},{"name":"MQTT","optional":true},{"name":"OCR","optional":true},{"name":"ONNX","optional":true},{"name":"ONNX Runtime","optional":true},{"name":"OpenCV","optional":true},{"name":"OpenVINO","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Quantization","optional":true},{"name":"Rest API","optional":true},{"name":"Sensor Fusion","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true},{"name":"TensorRT","optional":true},{"name":"Transformers","optional":true},{"name":"YOLO","optional":true}],"status":"live","first_seen_at":"2026-09-10T13:58:44Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-10-28T04:21:53Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":47},"description":"Project Role : Data ArchitectProject Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration.\nMust have skills : Edge Computing\nGood to have skills : NA\nMinimum 12 year(s) of experience is required\nEducational Qualification : 15 years full time education\nSummary:\nAs an Edge Computing and Computer Vision Architect/Manager, you will own the architecture and technical delivery of complex Edge AI solutions involving cameras, sensors, AI/ML models, edge compute platforms and cloud systems. You will lead technology and hardware selection, solution architecture, performance optimization and large-scale deployment while providing technical leadership to engineering teams and engaging with client and product stakeholders.\nRoles & Responsibilities:\nArchitect end-to-end Edge AI and Computer Vision solutions covering cameras, sensors, edge compute, AI inference, applications, actuators and cloud platforms.\nDefine edge architecture and select appropriate hardware based on compute, Graphics Processing Unit (GPU)/Neural Processing Unit (NPU) capability, power, thermal, environmental, connectivity and Total Cost of Ownership (TCO) requirements.\nEvaluate platforms such as NVIDIA Jetson, industrial x86 PCs, embedded System-on-Chip (SoC) platforms and dedicated AI accelerators.\nDefine camera architecture involving RGB (Red-Green-Blue), thermal/infrared, low-light, stereo, depth, Time-of-Flight (ToF) and specialized imaging technologies.\nArchitect sensor and actuator integration involving LiDAR (Light Detection and Ranging), radar, ultrasonic sensors, Inertial Measurement Units (IMUs), Programmable Logic Controllers (PLCs), motors, relays and industrial equipment.\nLead selection and design of Computer Vision solutions for object detection, segmentation, tracking, classification, Optical Character Recognition (OCR), pose estimation, anomaly detection, activity recognition and depth estimation.\nEvaluate model architectures including YOLO, SSD, Faster R-CNN, Mask R-CNN, DETR, U-Net, Vision Transformers (ViTs) and emerging Vision-Language Models (VLMs).\nDefine model optimization strategies including quantization, pruning, knowledge distillation, FP16/INT8 inference and hardware-specific acceleration.\nArchitect high-performance video and inference pipelines using OpenCV, GStreamer, NVIDIA TensorRT, NVIDIA DeepStream, Intel OpenVINO, ONNX Runtime or equivalent platforms.\nDefine camera interface and interoperability strategies using USB, MIPI-CSI (Mobile Industry Processor Interface - Camera Serial Interface), GigE Vision, RTSP (Real-Time Streaming Protocol), ONVIF and other relevant protocols.\nDefine requirements for camera calibration, multi-camera synchronization, sensor fusion and image/video preprocessing.\nArchitect edge solutions supporting local/offline operation, intermittent connectivity, data residency and edge-to-cloud synchronization.\nDefine secure edge architectures including secure boot, device identity, certificate management, encrypted communication, access control and protection of AI models and Intellectual Property (IP).\nDefine device lifecycle capabilities including provisioning, fleet management, Over-the-Air (OTA) software and model updates, remote monitoring, observability, health management and rollback.\nLead architecture and technical delivery from Proof of Concept (PoC) through pilot and large-scale production rollout.\nDesign solutions capable of supporting hundreds or thousands of cameras and edge devices across distributed locations.\nDefine technical Key Performance Indicators (KPIs) covering accuracy, latency, Frames Per Second (FPS), throughput, reliability, bandwidth, power and operational performance.\nLead architecture reviews, design reviews, technology evaluations and technical risk assessments.\nProvide technical leadership, mentoring and guidance to engineering teams.\nWork with product management, business teams and clients to translate business requirements into scalable technology solutions and roadmaps.\nProfessional & Technical Skills:\nMust To Have Skills: Strong architecture and hands-on expertise in Edge Computing, Computer Vision and Machine Learning.\nStrong knowledge of edge hardware architectures covering Central Processing Unit (CPU), GPU, NPU and dedicated AI accelerator technologies.\nDeep understanding of camera technologies, optics, image sensors, resolution, frame rate, Field of View (FoV), thermal imaging, low-light performance and camera selection.\nStrong knowledge of modern Computer Vision model architectures and their suitability for different use cases.\nExperience with PyTorch, TensorFlow and Open Neural Network Exchange (ONNX) ecosystems.\nStrong understanding of model optimization and inference acceleration on resource-constrained edge platforms.\nExperience with Python, C/C++, Linux, Docker and containerized edge applications.\nStrong understanding of video processing, camera pipelines and real-time inference architectures.\nExperience with edge-to-cloud architectures, MQTT (Message Queuing Telemetry Transport), REST APIs and Internet of Things (IoT) platforms.\nUnderstanding of Machine Learning Operations (MLOps), dataset lifecycle, annotation, model versioning, deployment, monitoring and model drift.\nStrong knowledge of edge security, remote device management and fleet lifecycle management.\nExperience designing for real-world environmental challenges such as lighting variations, weather, vibration, motion blur, occlusion and camera movement.\nAbility to make architecture trade-offs across accuracy, latency, hardware cost, power, bandwidth, reliability, scalability and Total Cost of Ownership.\nStrong client-facing communication, technical leadership and solution consulting skills.\nAdditional Information:\nThe candidate should have minimum 12 years of overall technology experience with strong experience in Edge Computing, Computer Vision and AI/ML solutions.\nCandidate should have demonstrated experience architecting and delivering Computer Vision solutions from Proof of Concept through large-scale production deployment.\nStrong preference for candidates who have experience with deployments involving hundreds or thousands of cameras, sensors or distributed edge devices.\nCandidate should have experience making hardware, camera, AI model and platform architecture decisions rather than focusing only on AI model development.\nExperience in industrial, manufacturing, transportation, automotive, retail, robotics, surveillance or smart infrastructure domains will be preferred.\nExperience leading engineering teams and interacting with senior client stakeholders is expected.\nThis position is based at our Bengaluru office.\nA 15 years full time education is required.\n15 years full time educationAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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